Teaching AI Ethics Through Everyday Questions About Fairness and Sustainability

Artificial intelligence (AI) can help people sort information, recognise patterns and make predictions. But an AI system can also make mistakes or affect people differently. Learning about AI therefore involves more than understanding how a tool works: students can also ask whether it is fair, useful and being used responsibly.

These questions suit classroom conversations and family discussions. They do not require students to create accounts or share personal information with an AI tool. The activities below are suggestions for building AI literacy and critical thinking, not a description of official BAIO exam content.

What the supplied source says

A Raspberry Pi Foundation page describes a research study involving computing teachers in England, Scotland and Wales. It focuses on teaching AI ethics and sustainability to lower-secondary students. The page reports that a review of earlier interventions found frequent attention to fairness and privacy, while sustainability and some other ethical ideas appeared less often. The proposed study aims to help teachers and students examine AI’s social and environmental impacts. This is a UK initiative, not a BAIO programme or part of the Indian curriculum.

Start with questions students can understand

Ethics means thinking about what is right, fair and responsible. Sustainability means considering how choices affect resources and the environment over time. These ideas may sound large, but students can begin with familiar questions: Who benefits? Who might be left out? What information is needed? Could there be another way to solve the problem?

For younger learners, use a familiar school example. Imagine a class is choosing books for a reading corner. A computer system suggests books based on students’ past choices. It may be helpful, but it might keep recommending the same kinds of books. Ask students whether the suggestions give everyone a chance to discover something new. This is a hypothetical discussion, not a claim about a real system.

Suggested activities: explore fairness, privacy and impact

1. Try a paper-based “sorting system”

Give a small group a set of fictional book cards, each with simple details such as topic, reading level and language. Ask students to sort the cards according to one rule, such as “show books about animals first”. Then change the rule or remove one detail and notice how the results change.

• Which books appeared near the top, and which did not?
• Would the same rule work well for every student?
• What information would help make the suggestions more useful?
• Could collecting extra information create privacy concerns?

Explain that this is a simplified model for discussion. Real AI systems can be much more complex, and this activity does not reproduce how a particular product works.

2. Look for missing voices

Ask students to imagine that a system has learned from examples of only a few kinds of books, voices or experiences. If it has not encountered enough variety, its results may not work equally well for everyone. In computing, the information used to teach a system is often called training data. A dataset that is too limited or unrepresentative can contribute to biased results.

Invite students to make a “who might be missing?” checklist. They might consider different languages, abilities, interests or experiences. The aim is not to assume that every system is biased, but to practise checking whose needs have been considered and what evidence would be needed to judge a result.

3. Add a sustainability question

Digital services depend on physical resources, such as devices and the infrastructure that runs them. The supplied source highlights that the environmental impact of AI has received less attention in some learning interventions it reviewed. Students can use this as a reason to ask questions, not as proof that every AI task has the same environmental cost.

Try a short discussion: “Before using an AI tool for a task, what should we consider?” Students might suggest whether it is necessary, whether a simpler method would work, and whether a trusted adult has approved its use. Avoid asking children to estimate energy use unless you have reliable information for the specific system.

Support thoughtful discussion at home or school

Parents and teachers do not need to know every technical detail to guide a useful conversation. Ask students to explain their reasoning, welcome uncertainty and separate what they know from what they are guessing. If a tool gives an answer, encourage them to check it against a reliable book, lesson resource or adult’s guidance.

• Protect privacy: use fictional examples and do not enter a child’s name, contact details, photographs or school information into an AI tool.
• Respect age rules: do not ask a child to create an account; if a digital demonstration is considered, an adult should check the tool’s age requirements and supervise it.
• Keep people responsible: discuss why a person should review important decisions rather than accepting a computer’s suggestion automatically.
• Make room for different views: ask students to give reasons and listen to classmates before deciding what seems fair.

A practical takeaway

AI literacy grows when students practise asking careful questions, not when they simply accept a system’s answer. A paper sorting activity, a privacy check or a discussion about resources can help learners connect computing with real choices. Keep examples age-appropriate, protect personal information and treat uncertainty as a reason to investigate further.